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dc.contributor.authorRached, Nadhir B.
dc.contributor.authorBenkhelifa, Fatma
dc.contributor.authorKammoun, Abla
dc.contributor.authorAlouini, Mohamed-Slim
dc.contributor.authorTempone, Raul
dc.date.accessioned2017-06-05T08:35:48Z
dc.date.available2017-06-05T08:35:48Z
dc.date.issued2015-01-07
dc.identifier.urihttp://hdl.handle.net/10754/624084
dc.description.abstractEstimating the probability that a sum of random variables (RVs) exceeds a given threshold is a well-known challenging problem. Closed-form expressions for the sum distribution do not generally exist, which has led to an increasing interest in simulation approaches. A crude Monte Carlo (MC) simulation is the standard technique for the estimation of this type of probability. However, this approach is computationally expensive, especially when dealing with rare events. Variance reduction techniques are alternative approaches that can improve the computational efficiency of naive MC simulations. We propose an Importance Sampling (IS) simulation technique based on the well-known hazard rate twisting approach, that presents the advantage of being asymptotically optimal for any arbitrary RVs. The wide scope of applicability of the proposed method is mainly due to our particular way of selecting the twisting parameter. It is worth observing that this interesting feature is rarely satisfied by variance reduction algorithms whose performances were only proven under some restrictive assumptions. It comes along with a good efficiency, illustrated by some selected simulation results comparing the performance of our method with that of an algorithm based on a conditional MC technique.
dc.titleAn Efficient Simulation Method for Rare Events
dc.typePoster
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentElectrical Engineering Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences & Engineering (CEMSE)
dc.conference.dateJanuary 6-9, 2015
dc.conference.nameAdvances in Uncertainty Quantification Methods, Algorithms and Applications (UQAW 2015)
dc.conference.locationKAUST
kaust.personRached, Nadhir B.
kaust.personBenkhelifa, Fatma
kaust.personKammoun, Abla
kaust.personAlouini, Mohamed-Slim
kaust.personTempone, Raul
refterms.dateFOA2018-06-14T02:24:42Z


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